Panel Data Research Center, Keio University
PDRC Discussion Paper Series【PDRC Research Series on JHPS Second Generation Supplement】
Intergenerational Correlation of Household Wealth: Evidence from the JHPS
Second Generation Supplement
Michio Naoi, Miki Seko, Kazuto Sumita, Takuya Ishino
31 March, 2021
DP2020-011
https://www.pdrc.keio.ac.jp/en/publications/dp/7048/

Panel Data Research Center, Keio University
2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan
info@pdrc.keio.ac.jp
31 March, 2021

【PDRC Research Series on JHPS Second Generation Supplement】
Intergenerational Correlation of Household Wealth: Evidence from the JHPS Second Generation
Supplement
Michio Naoi, Miki Seko, Kazuto Sumita, Takuya Ishino
PDRC Keio DP2020-011
31 March, 2021
JEL Classification: D31; D64; J62
Keywords: Household wealth; Intergenerational Correlation; Gifts and inheritance; Parent-childsurveyAbstract
This paper investigates the intergenerational correlation of household wealth and its determinants
using the Japan Household Panel Survey (JHPS) and its Second Generation Supplement (JHPSG2). Our empirical findings are summarized as follows: (1) the marginal effect of parental financial
wealth on their children's wealth is about 0.10 to 0.13, (2) the intergenerational correlation ofhousehold wealth is partly, albeit to a lesser extent than previous findings, determined by children's
education and income, and (3) the impact of parental wealth on homeownership among children islargely explained by direct wealth transfers across generations. The paper also investigates therelationship between future inheritance/gifts and the economic status of the child generation,
showing that (1) future inheritance/gifts of financial wealth is largely unrelated to the economic
status of the child generation, and (2) future inheritance/gifts of housing is negatively correlatedwith the economic status of the child generation.

Michio Naoi
Faculty of Economics, Keio University
2-15-45 Mita, Minatoku, Tokyo
naoi@econ.keio.ac.jp
Miki Seko
Institute of Political Science and Economics, Faculty of Economics, Musashino University
3-3-3 Ariake, Koto-ku, Tokyo
seko@econ.keio.ac.jp
Kazuto Sumita
Faculty of Economics, Toyo University
5-28-20 Hakusan, Bunkyo-ku, Tokyo
sumita@toyo.jp

Takuya Ishino
Faculty of Economics, Kanazawa Seiryo University
10-1 Ushi, Gosho-machi, Kanazawa-shi, Ishikawa
ishino@seiryo-u.ac.jp

Acknowledgement: We gratefully acknowledge the Panel Data Research Center at Keio University(PDRC) for generously providing us with the Japan Household Panel Survey (JHPS) and the Second
Generation Supplement (JHPS-G2). This paper was presented at the workshop of the JHPS Second
Generation Supplement (March 10, 2021) and JSPS Kakenhi workshop (March 12, 2021). We also
acknowledge comments and suggestions from Tsunao Okumura (Yokohama National University)and the participants at two workshops. This work was supported by JSPS KAKENHI Grant Numbers
17H00988 and 17H06086.

Intergenerational Correlation of Household Wealth:
Evidence from the JHPS Second-Generation Supplement*
Michio Naoi †, Miki Seko ‡, Kazuto Sumita §, Takuya Ishino **July 8, 2021
Abstract
This study investigates the intergenerational correlation of household wealth and its determinants using the Japan
Household Panel Survey and its second-generation supplement. Our main empirical findings are as follows: (1)The marginal effect of parents’ financial wealth on their children’s wealth is about 0.10 to 0.13, (2) theintergenerational correlation of household wealth is partly, albeit to a lesser extent than previous findings,
determined by children’s education and income, and (3) the impact of parental wealth on homeownership amongchildren is largely explained by direct wealth transfers across generations. The study also investigates therelationship between future inheritance/gifts and the economic status of the child generation, finding that (1) future
inheritance/gifts of financial wealth are largely unrelated to the economic status of the child generation and that(2) future inheritance/gifts of housing are negatively correlated with the economic status of the child generation.
Keywords: Household wealth; intergenerational correlation; gifts and inheritance; parent-child survey
JEL No.: D12, D31, D64, J62*

The JHPS Second Generation Survey Research Progress Report Meeting (March 10, 2021) and the JHPS Second Generation Survey
Research Progress Report Meeting (March 12, 2021) were supported by the Keio Center for Panel Survey Design and Analysis. We
would like to express our gratitude to Dr. Tsunao Okumura (Yokohama National University) and the participants for their valuablecomments on our report at the Grant-in-Aid for Scientific Research workshop (“Elucidation of Intergenerational and Interregional
Mismatch in the Housing Market: Economic Analysis Using Panel Data,” March 12, 2021). This work was supported by JSPS Grantsin-Aid for Scientific Research 17H00988 and 17H06086.
† Keio University (Email: naoi@econ.keio.ac.jp)‡ Musashino University (Email: seko@econ.keio.ac.jp)§ Toyo University (Email: sumita@toyo.jp)** Kanazawa Seiryo University (Email: ishino@seiryo-u.ac.jp)

11. Introduction
The concentration of household wealth and widening inequality have become important policy issues
in countries around the world. Recent empirical analyses of long-term estimates of wealth inequality
have generally indicated that wealth inequality has tended to increase since the 1980s (Katic and Leigh,2016; Alvaredo et al., 2018; Kuhn et al., 2020; Garbinti et al., 2021).
Several studies have examined the impact on macroeconomic wealth inequality of intergenerationaltransfers of wealth through inheritance and gifts. For example, using an overlapping generations model,
De Nardi (2004) shows that voluntary bequests and the transmission of earnings ability play animportant role in explaining the observed wealth distribution. Piketty and Zucman (2015) also showthat inherited wealth accounted for 55%–65% of the total wealth in France in 2010 and that this sharehas been increasing since the 1970s. However, there have been few examinations using individual dataof the way in which wealth concentration and inequality are maintained across generations, partly
because of the limitations of available data.
Most of the analyses that have dealt with the intergenerational transmission of economic disparities
have focused on the income levels and occupations of parents and children. 1 A representative example
of such an analysis is the measurement of the intergenerational elasticity of earnings. For example, inJapan, Ueda (2009) and Lefranc et al. (2014) estimate the intergenerational elasticity of earnings. By
contrast, only a few studies have estimated the intergenerational elasticity of wealth holdings using
individual data (Charles and Hurst, 2003; Arrondel, 2013; Kubota, 2017).
This study uses newly collected panel data on parents and children to conduct two main analyses. In
the first analysis, we present descriptive evidence of wealth distribution and transition across twogenerations. From this perspective, Kubota (2017), who also used a parent-child survey to measure
the intergenerational elasticity of wealth, is an important previous study. Our analysis is novel in thatit extends the analysis not only to financial wealth but also to homeownership as a real asset, and byusing detailed information on the parental generation, we conduct a more in-depth analysis of thepathways that explain the intergenerational correlation of wealth. Another contribution of this study isthat it takes advantage of the characteristics of a panel survey to conduct an analysis that considers the
problem of measurement error in wealth holding.
When considering the issue of intergenerational correlation of household wealth, the role of gifts andinheritance is significant, as pointed out by Piketty (2000) and others. However, our first analysis isbased on parent-child pairs in which at least one of the parents is still alive, so we cannot fully examine
the effect of inheritance on the wealth holdings of the child generation. With this in mind, the second
analysis examines how the likelihood of future inheritance (and gifts) is related to the current economic
status of children.
1

See also Bowles and Gintis (2002) and Black and Devereux (2011) for a survey of intergenerational correlations ofsocioeconomic attributes of parents and children.

2

The results of this study can be summarized as follows: The first analysis, which measures theintergenerational correlation of household wealth, shows that (1) the marginal effect of parental wealthon child wealth is about 0.10–0.13, taking into account the age and basic sociodemographic
characteristics of parents and children; (2) the intergenerational correlation of financial wealth ispartially explained by factors such as the human capital accumulation and income level of the offspring,but its magnitude is smaller than that of existing studies in the United States; and (3) the effect ofparental wealth on the child’s housing wealth (i.e., homeownership) is largely explained by past andfuture intergenerational transfers. The second analysis, which examined the relationship between theeconomic status of the child generation at the time of the survey and future inheritance and gifts,
revealed that (1) future inheritances and gifts of financial wealth have a strong positive correlation
with the asset holdings of the parent generation at the time of the survey but are generally unrelated tothe economic status of the child generation, and (2) future inheritance and gifts of housing depend on
both the asset holding status of the parent generation and the economic status of the child generation
at the time of the survey. In other words, the children with lower household income and education tend
to benefit from future housing inheritance as parental wealth increases.
The remainder of this paper is organized as follows: Section 2 presents an overview of the survey andits second-generation supplement and describes the main variables used in the analysis. Section 3
reviews the standard analytical framework for intergenerational correlations in household wealth andpresents the empirical results. Section 4 concludes the paper.

2. Data and Variables
2.1 Japan Household Panel Survey and Second-Generation Supplement
In this study, we use the Japan Household Panel Survey and its second-generation supplement toconstruct data on parent-child pairs. In the following, the main survey, the Japan Household Panel
Survey, will be referred to as the JHPS/KHPS, and its second-generation supplement will be referred
to as JHPS-G2.
The JHPS/KHPS is a household panel survey of adult males and females that was originally conducted
as two independent panel surveys by the Panel Data Research Center (PDRC) at Keio University. The
first survey was the Keio Household Panel Survey (KHPS), which has been conducted annually since2004. The second survey was the JHPS, which has been conducted annually since 2009. The initialsample size was 4,005 households for the KHPS and 4,022 households for the JHPS. 2 These two

2

In addition, the KHPS was supplemented by a new sample of 1,419 and 1,012 households in 2007 and 2012,
respectively, and the JHPS was supplemented with a new sample of 2,203 households in 2019. In both surveys, theselection of the target population was conducted using a stratified two-stage random sampling method, with the firststratum being the region/city size and the second stratum being the census tract, making the sample representative of
the entire country at the time of the first survey. The population in the first survey comprised males and females aged
20–69 in the KHPS, and males and females aged 20 or older in the JHPS.

3

surveys merged in 2014. The JHPS/KHPS provides a wide range of individual characteristics, such as
the employment, income, education, and health status of the survey respondents and their spouses, aswell as household characteristics, such as consumption, income, and financial and housing wealth.
The first JHPS-G2 was conducted in 2017 as a supplementary survey to the JHPS/KHPS. The firstsurvey was conducted by the Center for Research on Equal Opportunity for Children (CREOC) at
Keio University. The targeted respondents were children of JHPS/KHPS subjects and at least 18 years
old at the time of the survey. The survey proceeded as follows: First, JHPS/KHPS subjects withchildren aged 18 years or older were informed of the JHPS-G2 survey implementation plan and asked
to provide their children’s residential addresses. Second, a request for survey cooperation with the
JHPS-G2 was mailed to the targeted children, and then a mail or web-based survey was conductedwith those who gave consent.
The second wave of JHPS-G2 was conducted in March 2019 in collaboration with the CREOC and
PDRC. As in the first wave of the survey, the targeted respondents were children of JHPS/KHPS
subjects who were at least 18 years old at the time of the survey. The survey procedure was the same
as for the first wave. However, among the respondents to the first survey in 2017, those who gave
permission to be contacted in the future were directly asked to participate in the survey. As a result,
1,001 subjects responded to the first wave of the survey, and 1,072 subjects responded to the second
wave. In principle, the survey items of the JHPS-G2 follow those of the JHPS/KHPS so that children’s
responses to these items are comparable to those of parents obtained from the JHPS/KHPS. However,in comparison to the JHPS/KHPS, the JHPS-G2 includes a limited set of survey items, covering only
basic information on the subject's education, employment, and health, as well as the household’s
income, consumption, and financial and housing wealth. For married children, basic information about
their spouses was also obtained, such as their age, education, and employment status.
We constructed a dataset on parent-child pairs by connecting the JHPS/KHPS and JHPS-G2.
Compared to other typical household panel surveys, the JHPS/KHPS is unique in its ability to provide
a detailed picture of households’ asset holdings. Specifically, the JHPS/KHPS provides information
on savings and securities holdings, mortgages, debts, and the values of owner-occupied houses. The
same information is also available for the JHPS-G2. By connecting the two surveys, it is possible tomeasure the wealth status of the two generations, parents and children.
The traditional intergenerational analysis is often based on cross-sectional data for either the parent orchild generation. For example, if the data are targeted at children, information about the parents is only
available for proxy responses by the children. In this case, information that is easy for the child toanswer, such as the parent's occupation, can be available, but information about the amount of assets
held, for example, is difficult to survey. In addition, there are few surveys that ask for detailed
information on asset holdings even if the design surveys both parents and children, and it can be said
that there are few datasets in Japan that make it possible to examine the relationship between parent
4and child asset holdings.
In the following analysis, the second JHPS-G2 survey conducted in 2019 was used as the main dataset
for the analysis, and by connecting JHPS/KHPS to this data using household ID as the key, a datasetof parent-child pairs with children as the unit of observation was constructed. Note that the first JHPSG2 survey does not include survey items on wealth holdings, so when using the wealth holdings of thechild generation, the analysis was effectively based on the second wave of the JHPS-G2.

2.2 Variables used in the analysis
Income and WealthFirst, the asset holdings of the two generations of parents and children, which is the main interest of
this study, were prepared as follows: For the parent generation, we measured net asset holdings basedon savings and marketable securities holdings, outstanding loans, and self-assessed values of theirhouses, as surveyed in the JHPS/KHPS. Specifically, we calculated the net worth of the parents’generation by subtracting the outstanding balance of loans, including mortgages, from the sum of theirfinancial wealth (savings and securities) and the self-assessed value of their houses. However, since
there are concerns about measurement errors in the balance of loans and the self-assessed value of
housing, we also use gross financial wealth (i.e., savings and securities holdings) as a measure ofparental wealth.
In the estimation of intergenerational correlations of income and wealth, there is a concern that
attenuation bias may occur due to measurement errors regarding parental income and wealth (Blackand Devereux, 2011). In the following analysis, we follow the standard method and use the average ofseveral previous years for parental income and asset holdings (Charles and Hurst, 2003). Specifically,using the characteristics of the JHPS/KHPS as a panel survey, we use the average of the three years(2016–2018) or five years (2014–2018) prior to the implementation of the 2019 survey.
For child wealth, we constructed variables from the JHPS-G2, which have the same asset-related
survey items as the JHPS/KHPS, so that the same asset-related variables can be measured for the childgeneration as for the parent generation. However, the response rates for outstanding loans and housing
assets were not particularly high. 3 For this reason, the following analysis focuses on the amount offinancial wealth held and whether or not the respondents owned their own homes as variables
representing the asset holdings of the child generation.
In addition, annual pre-tax household income was used for both parent and child income. For theparent generation, as in the case of the asset variable, the average household income for the preceding
three years (2016–2018) was used.

3 Of the sample of children available for analysis, 58.0% responded with the outstanding debt and 72.5% respondedwith the self-assessed value of the house.

5Gifts and Inheritance
As discussed in Section 1, direct transfers by inheritance and gifts may explain the intergenerationalcorrelation of wealth. On the basis of the information available from the JHPS-G2, we created three
types of variable. The first relates to past intergenerational transfers; the JHPS-G2 provides
information on financial assistance between parents and children that occurred in the year prior to thesurvey. These items capture the existence, amount, and purpose of financial assistance in the past year.
In the following analysis, the items “How much financial aid did you receive from your parents in thepast year?” and “How much financial aid did you give to your parents in the past year?” were used todetermine the amount of aid from parents to children and from children to parents, respectively. 4 Whilethese variables have the advantage of being able to measure direct financial transfers between parents
and children, they also have some drawbacks. First, parental support here includes not only thatprovided by the parents of the JHPS-G2 respondents themselves (JHPS/KHPS subjects) but also thatprovided by the parents of their spouses. In addition, from the perspective of explaining theintergenerational correlation of wealth, it would be desirable to use the accumulated amount up to thetime of the survey, but this item only provides information on transfers in the year prior to the survey.
To account for this measurement problem, we created a second variable, a dummy variable indicatingthat one of the parents was deceased. If one of the parents was deceased at the time of the survey, thesubject may have inherited from a parent in the past.
The third variable is related to future intergenerational transfers. In the JHPS-G2, respondents wereasked whether they expected future gifts and/or inheritance from their parents. There are separate
survey items for future transfers of financial wealth and housing. We created dummy variables forfinancial and housing transfers that take the value of 1 when future inheritance or gifts are expected.
Other Control Variables
In addition to the variables explained above, we also used parent and child characteristics such as age,marital status, education, and place of residence. We used the attributes of the respondents of the JHPSG2 for age and educational background of the children. 5 The age of the younger parent was used forthe parents’ age. Father’s education was used for education. For residence, we created a dummy
variable indicating the city and county size (government-designated city, other city, town, or village)
4

Financial support between parents and children in the JHPS-G2 includes support for education and housing purchase
but does not include support due to inheritance.
5 It should be noted that the head of the household in a married-couple household does not necessarily match the
respondent in the JHPS-G2. Since the analysis in this paper targets asset holdings and income at the household level, it
would be appropriate to use the attributes of the head of the household, but since the JHPS-G2 asks very little about
the attributes of spouses, we decided to use the attributes of the respondents themselves. However, we have confirmedthat the results obtained are almost the same even if the sample is divided by the gender of the JHPS-G2 respondents.

6

of the residence of each parent and child, as well as a dummy variable indicating whether the parent
and child lived together or in close proximity (same city, town, or village, same prefecture).
The sibling composition of children may also have an effect when analyzing intergenerational transfers,
such as gifts and inheritance. For this reason, we created variables representing the number of siblings
and whether or not the survey targets in JHPS-G2 were only children.

2.3 Descriptive statistics
Table 1 shows the descriptive statistics for the parent and child samples, showing that the proportionof females in the child sample was higher than in the parents sample. In addition, the percentage ofparents and children living together was also relatively high. According to the 2015 Census, thepercentage of individuals aged 20–59 living with their parents was about 32%, around the same as in
the JHPS-G2. However, since the co-residence rate in the census included not only one’s own parents
but also one’s spouse’s parents, the co-residence rate with one’s own parents was approximately 16%,
based on simple calculations. By contrast, the cohabitation rate for the JHPS-G2 sample (Table 1) was
27.0%. The impact of these sampling characteristics on the estimation results is discussed later.

3. Empirical Model and Estimation Results
In this section, we present a standard framework for analyzing intergenerational correlations inhousehold wealth and show the results of our analysis using the JHPS-G2. The analysis consists ofthree major parts. In the first part, we examine the current state of intergenerational mobility in termsof wealth holdings. Specifically, we calculate an intergenerational transition matrix based on theamount of financial wealth held by parents and children. For comparison, we also examine theintergenerational transition matrix of parents and children’s annual household income. In the second
analysis, we use a regression analysis to estimate the intergenerational correlation of wealth holdings.
This is a standard method for analyzing intergenerational correlations in income, and in its simplest
formulation, it is obtained as the coefficient of a regression of children’s wealth on their parents’ wealth.
In the analysis, we add additional control variables that mediate the intergenerational correlation in
wealth, such as the education level of the child generation, income, and past and futureintergenerational transfers, to see how the magnitude of the intergenerational correlation changes.
Finally, in the third analysis, we explore the relationship between children's economic status and futureintergenerational transfers. We present the results of the first and second analyses in Sections 3.1 and
3.2, and the results of the third analysis in Section 3.3.

3.1 Intergenerational correlation of household wealth
Table 2 shows the intergenerational transition matrix for each quartile of the financial asset holdingsof the parent and child generations. Each row of the table represents the quartile level of financial
7

wealth held by the parent generation, and the column represents the quartile level of the childgeneration. Since the sum of the rows is standardized to 100, the value in each row indicates the
distribution of the financial wealth holdings of the children’s generation, conditional on the financial
wealth held by the parents. In the actual calculations, we took into account the fact that the amount offinancial wealth held by households depended on their age and marital status and conducted ouranalysis using the following procedure. First, using a sample of parents and children, we regressed theamount of financial wealth held on the subject’s age and its square, gender, and marital status, andcalculated the residuals. Then, on the basis of the respective estimation results, we divided the sample
into quartiles based on the size of the residuals. Therefore, the results shown in Table 2 indicate theintergenerational stratification of financial asset holdings adjusted for age, sex, and marital status.
From Table 2, we can point out several aspects of intergenerational mobility in financial wealthholdings. First, there is a clear positive correlation between parents and children’s financial wealthholdings. For example, when parents’ financial wealth is below the 25th percentile, 42.4% of thechildren also stay below the 25th percentile, whereas when the parents’ financial wealth is above the75th percentile, only 14.4% do. Kubota (2017) found these figures to be 38% and 15%, respectively,
showing roughly similar results. The percentage of parents and children staying in the same asset
quartile is substantially larger for parents both at the top and bottom of the wealth distribution.
Second, we see that the intergenerational mobility of financial wealth is smaller than that of householdincome. Table 3 shows the results of the intergenerational transition matrix of pre-tax householdincome using the same method for comparison. 6 A comparison of Tables 2 and 3 shows that the
proportion of parents and children who remain in the same asset/income quartile is higher in terms of
the amount of financial wealth held, especially at the top and bottom of the parental income/asset
distribution.
To further examine the relationship between the wealth holdings of the parent and child generations,an analysis using regression analysis is conducted in the following section. The empirical model is asfollows:
𝑦𝑦𝑐𝑐 = 𝛼𝛼 + 𝑓𝑓�𝑤𝑤𝑝𝑝 � + 𝛽𝛽𝑐𝑐 𝑥𝑥𝑐𝑐 + 𝛽𝛽𝑝𝑝 𝑥𝑥𝑝𝑝 + 𝜀𝜀𝑐𝑐(1)

where 𝑐𝑐 is the index representing the child, 𝑝𝑝 is the index representing the parent, and 𝑤𝑤𝑝𝑝 represents

the amount of wealth held by the parents. In the following analysis, we used the amount of financial

wealth held (savings + securities) or net worth (savings + securities + self-assessed value of housing
liabilities); 𝑦𝑦𝑐𝑐 represents child characteristics influenced by parental wealth. In the following empirical6

In preparing Table 3, the sample was limited to cases in which the younger of the parents was 65 years old or younger,

taking into account the inclusion of retired parents.

8

analysis, we mainly focus on the effect of parental wealth on child wealth, measured either by savings,
financial wealth holdings, or homeownership of the child generation, but we also estimate the effects
on various aspects of child generation, including college attendance, household income, savings rate,
and past and future transfers.
There may be a non-linear relationship between 𝑤𝑤𝑐𝑐 and 𝑦𝑦𝑐𝑐 . For this reason, in estimating Equation (1),

we assume 𝑓𝑓 as a quadratic function of 𝑤𝑤𝑝𝑝 ; 𝑥𝑥𝑐𝑐 and 𝑥𝑥𝑝𝑝 are the attributes of the children and parents,

respectively. 7 For children, we used age and its square, gender, marital status, and dummy variable forco-residence with parents, and for parents, we used age and its square, gender, and marital status.

The estimation results of Equation (1) are summarized in Table 4. The table presents results from aseries of simple regressions in which different child attributes shown in the first column are regressedon parental wealth. The marginal effects of parental wealth are presented in Table 4. The results forthe other coefficients are omitted. The standard errors in parentheses are robust to correlations in theerror term between observations with the same parent. 8
Looking at the results using children’s savings and financial wealth holdings as the dependent
variables, both are significantly and positively associated with parental wealth. Comparing the results
for savings and financial wealth holdings of the child generation, the estimated marginal effect ofparental net worth is larger for the latter. This may be attributed to the non-negligible size of securities
holdings in households with a large amount of assets. Comparing the results using different measuresof parental wealth, the marginal effect is somewhat smaller when parental net worth is used. Looking
at the estimation results when using the financial asset holdings of the child generation as thedependent variable, the estimated marginal effect is approximately 0.10–0.13. The results indicate thatan additional 1 million yen increase in parental wealth (financial wealth holdings or net worth) leads
to an increase in the financial wealth holdings of the child generation of, on average, about 100,000 to
130,000 yen. This result is somewhat smaller than that of Fagereng et al. (2021), who used data from
Norway. 9 Table A1 presents the estimates of the intergenerational elasticity based on the results shownin Table 1. Our results show that the intergenerational elasticity of financial wealth between parent
and child generations ranges between 0.54 and 0.59, which is slightly larger than that found by Charles
and Hurst (2003) and Arrondel (2013), who conducted similar estimations. Parental wealth is also

7

Several existing studies assume a double-log model as the estimating equation equivalent to Equation (1) and interpretthe coefficient on the amount of parental assets as an estimate of intergenerational elasticity (Charles and Hurst, 2003;
Arrondel, 2013). In such a model, the analysis would be limited to a sample in which asset holdings are non-negative.
However, in the data used in this study, approximately 16.4% of the sample of children and 12.6% of the sample ofparents have zero financial asset holdings, and in order to include these samples in the analysis, the formulation in
Equation (1) was adopted. Alternative methods include performing an inverse hyperbolic transformation (Kubota,2017) or transforming the asset holdings of each parent and child into percentile ranks for analysis (e.g., Adermon etal., 2018; Boserup et al., 2018; Pfeffer and Killewald, 2018).
8 If a household of a JHPS/KHPS subject has more than one child in the age group covered by the JHPS-G2, the sample
used for estimation in Equation (1) will include siblings with the same parents.
9 According to Fagereng et al. (2021), the magnitude of the marginal effect of parental asset holdings ranges from 0.20
to 0.28 when the child is adopted, and from 0.47 to 0.58 when the child is not adopted.

9positively associated with child homeownership, but the relationship is weaker in terms of statisticalsignificance.
The above results indicate that there is a positive correlation between parent and child asset holdings
after controlling for factors such as parent and child age, child marital status and gender, and parent
and child cohabitation. There are several possible paths for this intergenerational correlation. The firstpath is the possibility that parental wealth holdings promote human capital accumulation in theirchildren through the relaxation of borrowing constraints, which in turn leads to increases in income
and wealth accumulation. The estimation results in Table 4 show that the education of children (college
degree or higher = 1) and household income are both significantly positively correlated with parental
net wealth holdings, which is consistent with the above possibility. The second path is the possibility
that the preference parameters (risk aversion and time discount rate) that govern the choice of risky
assets and the propensity to save are correlated between parents and children; thus, intergenerationalcorrelations also arise in asset holdings. Although it is difficult to test this possibility directly due todata limitations, Table 4 shows the results using the ratio of savings to annual household income as
the dependent variable for the propensity of the child to save. This confirms that parental asset holdings
are significantly and positively correlated with the savings ratio of the child. 10 The third path is throughdirect asset transfers from the parents. If parents who own large amounts of assets are transferring
assets to their children through gifts during their lifetime, this will directly lead to a positive
intergenerational correlation in asset holdings. For this possibility, we estimated the amount offinancial support from parents as the dependent variable in Table 4. As a result, parental net worth ispositively correlated with the amount of financial support from parents that occurred in the year before
the survey, which is consistent with the above possibility. In addition, children’s wealth accumulation
may be affected by expected future asset transfers from their parents. 11 In Table 4, we also analyzefinancial wealth and the possibility of future inheritance and gifts of housing as dependent variables,
and these also show positive correlations with parental wealth holdings.

3.2 Adding mediating variables
In this section, we conduct an analysis that extends the model in Equation (1) to examine the factors
behind the intergenerational correlation of household wealth. We check how the magnitude of themarginal effect changes by sequentially adding factors corresponding to the multiple paths describedin the previous section as mediating variables to the explanatory variables in Equation (1). Mediating
10

Because children's savings percentages may be directly affected by past asset transfers from parents, children’s
inheritance motives, and the level of asset holdings, caution should be exercised in interpreting these results as solely
attributable to correlations between parent and child preference parameters (Dynan et al., 2004). The JHPS/KHPS and
JHPS-G2 provide hypothetical question items to measure preference parameters such as time discount rate and risk
aversion, and these variables need to be examined in more detail.
11 Ishino et al. (2020) directly examine such a possibility. According to them, child households that may inherit theirparents’ housing tend to consume more, while child households that may inherit financial assets tend to save more.

10

variables include children’s education (college degree or higher = 1), household income, financial
support between parents and children, whether one of the parents is deceased, future inheritance/gifts,
and child’s savings ratio. Specifically, we estimated the following regression model by adding themediating variables 𝑧𝑧𝑐𝑐 in Equation (1)𝑦𝑦𝑐𝑐 = 𝛼𝛼 + 𝑓𝑓�𝑤𝑤𝑝𝑝 � + 𝛽𝛽𝑐𝑐 𝑥𝑥𝑐𝑐 + 𝛽𝛽𝑝𝑝 𝑥𝑥𝑝𝑝 + 𝛾𝛾𝑧𝑧𝑐𝑐 + 𝑢𝑢𝑐𝑐(2)

to examine the marginal effect of parental wealth holdings, 𝑤𝑤𝑝𝑝 . In Equation (2), we use the amount offinancial wealth and homeownership (owner-occupied = 1) of the child generation as the dependent
variable.

If, for example, the children’s human capital accumulation and the resulting higher income levels are
the factors explaining the intergenerational correlation of wealth, then the marginal effect of parental
wealth becomes smaller when we control for children’s education and income levels as an additional
mediating variable, 𝑧𝑧𝑐𝑐 . A similar analysis was conducted by Charles and Hurst (2003).

Table 5 presents the estimation results. The table presents the estimated marginal effects of parental
wealth 𝑤𝑤𝑝𝑝 on child wealth (financial wealth and homeownership). The mediating variables in the
regression are shown in the first column. Model [1] in the first row shows our baseline results,

presented in Table 4, without controlling for the mediating variables. The numbers shown in the “%”column shows how much of the parental wealth effect is accounted for by the set of mediating variables
included in each model compared to our baseline.
The findings indicate that by adding the child’s final education and household income as explanatory
variables, the estimated value of the marginal effect on 𝑤𝑤𝑝𝑝 becomes smaller. Specifically, when theamount of financial wealth held by the child is used as the dependent variable, the estimated value ofthe marginal effect becomes approximately 35% smaller, from 0.1016 to 0.0659. However, Charles

and Hurst (2003), who used data from the United States, found the coefficient estimate to be about
54% smaller, from 0.37 to 0.17, in a similar estimation, and the additional effects of children’s final
education and household income were small. One possible interpretation of this result is that thefinancial burden of attending college is relatively small in Japan compared to the U.S., and thatparental wealth ownership has less of an impact on children’s college education by easing borrowing
constraints. 12 The same result was confirmed when homeownership was used as an explanatory
variable, and the marginal effect was reduced by approximately 35%, from 0.0012 to 0.0007, by

12

On the other hand, the possibility of bias due to measurement error cannot be ruled out because the cross-sectional
values observed in the JHPS-G2 conducted in 2019 are used here as the household income of children. By contrast, inCharles and Hurst (2003), which used the PSID, information on household income of children was also available atmultiple time points, and estimates were made using historical averages. To deal with this problem, we can consider
using the projected annual household income of the child generation, and we will study this issue in more detail in the
future.

11adding children’s final education and annual household income as explanatory variables.
From the addition of more explanatory variables to the above models (Models [3] through [8]), thefollowing results are confirmed. First, when the amount of financial wealth held by children is usedas the dependent variable, the marginal effect on 𝑤𝑤𝑝𝑝 decreases almost monotonically. As a result, inthe case where all variables are added (Model [8]), the estimated value is 0.0345, which isapproximately 66% smaller than the original value, and loses its statistical significance. These changes
are similar to the results of Charles and Hurst (2003). 13
On the other hand, when child homeownership is the dependent variable, the marginal effect estimate
becomes insignificant by adding the household income of the child generation as an explanatory
variable. In addition, we find that the values become significantly smaller by adding the death of oneof the parents (past inheritability) and the possibility of future inheritance or gifts as explanatory
variables in particular. This suggests that homeownership as a real asset is strongly affected by directintergenerational transfers, such as inheritance and gifts.

3.3 Future inheritance/gifts
The results of the previous section show that the wealth holdings of the child generation at the time of
the JHPS-G2 survey are positively correlated with parental wealth. Since the subjects of JHPS-G2 areindividuals with at least one parent still alive, they may have gifts or inheritance from their parents inthe future. Therefore, future inheritance (or gifts) from parents may affect the eventual wealthdistribution of the child generation.
In this section, with this in mind, we examine the relationship between the likelihood of future
inheritance and the economic status of children at the time of the survey. If households that areeconomically disadvantaged at the time of the survey have a lower likelihood of gifts or inheritancein the future, the intergenerational wealth transfers may increase the wealth inequality of the childgeneration more than indicated in the previous section. Conversely, if households that areeconomically disadvantaged are more likely to have gifts or inheritance in the future, thenintergenerational wealth transfers can mitigate the wealth inequality of the child generation.
Our model of the likelihood of future inheritance is given as follows:

13

𝑃𝑃𝑃𝑃(𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑐𝑐 = 1) = 𝛼𝛼 + 𝑔𝑔�𝑤𝑤𝑝𝑝 , 𝑦𝑦𝑐𝑐 � + 𝛽𝛽𝑐𝑐 𝑥𝑥𝑐𝑐 + 𝛽𝛽𝑝𝑝 𝑥𝑥𝑝𝑝 + 𝜈𝜈𝑐𝑐

(3)

On the other hand, there are still some problems related to the measurement of variables in the results of our analysis.
For example, asset transfers from parents in the past are considered to be one of the important factors in theintergenerational correlation of assets, but since the JHPS-G2 can only capture financial transfers that occurred in thepreceding year, it may not fully reflect these factors. In addition, the financial transfers here include not only those by
the parents of the JHPS/G2 subjects (JHPS/KHPS subjects) but also those by the parents of their spouses, which may
also have an impact. We also cannot rule out the possibility that factors not taken into account here, such as genetic
correlations of ability and skill transmission between parents and children (which affect the growth rate of income),
intergenerational correlations of occupation, and business succession, may be the pathway for intergenerationalcorrelations of asset holdings (Okumura and Usui, 2016; Fagereng et al., 2021).

12

where 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑠𝑠𝑐𝑐 is a dummy variable indicating that a child can expect future inheritance from theirparents, 𝑤𝑤𝑝𝑝 indicates parental net worth, and 𝑦𝑦𝑐𝑐 is a variable representing the economic status of thechild generation measured by the current household income. The dummy variable for future
inheritance is defined separately for financial wealth and housing.

In Equation (3), future inheritance from parents depends on both parental net worth �𝑤𝑤𝑝𝑝 � and thechild’s economic status at the time of the survey. It is likely that wealthy parents will bequeath wealthto their children, and the current net worth of parents is positively associated with future inheritance.
The bequest decision can also be affected by a child’s economic status. For example, altruistic parents
might bequeath more to economically disadvantaged children. We expect such an altruistic divisionof bequests to be more likely when parents have sufficient net worth. By contrast, less wealthy parents
may have no room for an altruistic division of bequests. Consequently, our empirical model includes
parental net worth �𝑤𝑤𝑝𝑝 � , child’s economic status (𝑦𝑦𝑐𝑐 ) , and their interaction term �𝑤𝑤𝑝𝑝 × 𝑦𝑦𝑐𝑐 � as
explanatory variables, which is represented by 𝑔𝑔�𝑤𝑤𝑝𝑝 , 𝑦𝑦𝑐𝑐 � in Equation (3). We also control for thecharacteristics of parents and children ( 𝑥𝑥𝑝𝑝 and 𝑥𝑥𝑐𝑐 ), which include the number of siblings andhomeownership of JHPS-G2 subjects, in addition to variables such as sex, age, marital status, coresidence, and location of parents and children, as in the previous sections.

The results of the logit model estimation using Equation (3) are shown in Table 6. This table shows
the marginal effect of parental net worth on the probability of future gifts and inheritance, and how
this effect varies with the level of current household income of the children. Specifically, we evaluate
the average marginal effect of parental net wealth holdings for children in the bottom 10%, medianaverage, and top 10% of the income distribution. Columns [1] and [2] show the results when the future
inheritance of financial wealth is used as the dependent variable, whiles columns [3] and [4] show theresults when future housing inheritance is used as the dependent variable. In addition, we estimate themodel for the self-reported value of the parent’s house, which is expected to be inherited. These results
are presented in columns [5] and [6]. 14 In this case, we restricted our sample to children who expect
to inherit their parents’ houses.
Estimation results for the future inheritance of financial wealth (columns [1] and [2]) show thatparental net worth is significantly and positively associated with the likelihood of inheriting financial
wealth, regardless of the level of children’s current income. On the other hand, results on the future
inheritance of a parent’s house (columns [3] and [4]) show that parental net worth is also positively
associated with the probability of future housing inheritance, but these effects are more pronounced
for children with lower current income. The estimation results show that a one million yen increase inparental net worth increases the probability of housing inheritance by 0.18%–0.45% for children in

14 Estimates in columns [5] and [6] are based on linear regression models.

13

the bottom 10% of income distribution, whereas the corresponding estimates are almost zero and notstatistically significant for children in the top 10% of income distribution. Thus, as parental net worth
increases, the likelihood of inheriting a house in the future increases for economically disadvantaged
children. This result is consistent with Hirayama (2019), who showed that low-income children are
more likely to choose to live with their parents and inherit their houses, suggesting that housing
inheritance plays a role in mitigating wealth inequality.
The above results are also supported by the results when we use children’s education as an alternative
measure of a child’s economic status. We estimate models that allow for different effects of parental
net worth depending on the child's education (high school or less, junior/technical college,
college/graduate school). The results are presented in Table 7. Much as in Table 6, columns [1] and[2] of Table 7 show that parental net worth is positively associated with future inheritance of financial
wealth regardless of children's education levels. Columns [3] and [4] show that less educated children
are more likely to inherit housing as their parents' net worth increases.
Finally, the results on the value of parents’ houses to be inherited (columns [5] and [6] in Tables 6 and
7) show that the self-reported value of the house to be inherited tends to be higher as the child’s income
and education levels are higher and the amount of the parent’s wealth holdings increases. These results
suggest that, unlike the inheritability of housing, the value of inherited housing may be more favorable
for economically advantaged children.

4. Conclusion
Using the JHPS-G2, we created new individual-level data for parents and children. In addition to thebasic attributes of each parent and child, these data are unique in that they include detailed information
on wealth holdings. In this study, we use the data to measure the intergenerational correlation between
parents and children’s wealth holdings and discuss the potential factors that explain this correlation.
In addition, we confirm how the economic status of the child generation at the time of the survey isrelated to the likelihood of inheritance from parents.
The main results of the analysis are as follows: First, we confirmed the positive correlation between
the amount of financial wealth held by parents and children and found that the marginal effect ofparental wealth on child wealth is about 0.10–0.13. The magnitude of the corresponding
intergenerational elasticity of household wealth is approximately the same as or slightly larger thanthe values in previous studies in the U.S. and other countries. This result clearly shows theintergenerational correlation of household wealth in Japan. In addition, when we consider mediating
factors, such as the income and education of the child generation, intergenerational transfers of wealth,propensity to save, and location, as potential pathways to explain the correlation between parent andchild wealth holdings, the size of the marginal effect is reduced by up to 66%. This result suggests thatthe wealth holdings of the parental generation may affect the wealth accumulation of the child14

generation through human capital investment in children, direct wealth transfers, and correlations in
the propensity to save.
Second, parental net wealth holdings have been shown to be positively correlated with homeownershipby children, confirming the intergenerational correlation of household wealth not only with financial
wealth but also with real assets. In addition, the analysis considering the attributes of the childgeneration as a mediating variable suggests that the influence of parental wealth on homeownershipof the child generation may arise mostly through the direct intergenerational transfer of wealth.
Third, an analysis of the relationship between the economic status of the child generation at the timeof the survey and future inheritance from their parents showed (1) that the future inheritance offinancial wealth has a strong positive correlation with the wealth-holding status of the parent
generation at the time of the survey but is generally unrelated to the economic status of the childgeneration and (2) that the likelihood of inheriting a house depends on both the wealth-holding statusof the parent generation and the economic status of the child generation at the time of the survey, withthe child generation with a lower household income and education tending to have a higher likelihoodof inheriting a house as the wealth holding of the parent generation increases.
As mentioned in Section 1, there has been a dearth of microdata with detailed information on thewealth holdings of parents and children, and this situation has made it difficult to analyze theintergenerational correlation of household wealth in Japan. The main contribution of this study is thatit presents the current state of the intergenerational correlation of wealth holdings in Japan. However,there are some limitations to it and future issues that need to be addressed. One of the most significant
problems is related to the survey design of the JHPS-G2. The JHPS-G2 survey can only be conducted
if the parent generation (JHPS/KHPS subjects) provides the residential address of the child and thechild generation (JHPS-G2 subjects) gives consent. Therefore, the obtained sample of the childgeneration is not necessarily randomly selected, which may pose sample-selection issues. Specifically,
compared to the population average, the sample of children in the JHPS-G2 is more likely to be female
and to live with their parents. Although the direction and magnitude of the bias caused by this sample
selection are not necessarily clear, it is possible that our estimates of the intergenerational wealthcorrelation are biased upward. We believe that more careful consideration will be required.

References
Adermon, A., M. Lindahl, and D. Waldenström (2018) “Intergenerational Wealth Mobility and theRole of Inheritance: Evidence from Multiple Generations,” Economic Journal, 128(612), pp. F482F513.
Alvaredo, F., A. B. Atkinson, and S. Morelli (2018) “Top Wealth Shares in the UK over More than aCentury,” Journal of Public Economics, 162, pp. 26-47.
Arrondel, L. (2013) ‘Are "Daddy’s Boys’ Just as Rich as Daddy? The Transmission of Values Between
15

Generations, Journal of Economic Inequality, 11(4), pp. 439-471.
Black, S. E. and P. J. Devereux (2011) “Recent Developments in Intergenerational Mobility” in,Handbook of Labor Economics: Elsevier, 4b, pp. 1487-1541.
Boserup, S. H., W. Kopczuk, and C. T. Kreiner (2018) “Born with a Silver Spoon? Danish Evidenceon Wealth Inequality in Childhood,” Economic Journal, 128(612), pp. F514-F544.
Bowles, S. and H. Gintis (2002) “The Inheritance of Inequality,” Journal of Economic Perspectives,16(3), pp. 3-30.
Charles, K. K. and E. Hurst (2003) “The Correlation of Wealth Across Generations,” Journal of
Political Economy, 111(6), pp. 1155-1182.
De Nardi, M. (2004) “Wealth Inequality and Intergenerational Links,” Review of Economic Studies,71(3), pp. 743-768.
Dynan, K. E., J. Skinner, and S. P. Zeldes (2004) “Do the Rich Save More?,” Journal of Political
Economy, 112(2), pp. 397-444.
Fagereng, A., M. Mogstad, and M. Rønning (2021) “Why Do Wealthy Parents Have WealthyChildren?,” Journal of Political Economy, 129(3), pp. 703-756.
Garbinti, B., J. Goupille-Lebret, and T. Piketty (2021) “Accounting for Wealth-Inequality Dynamics:
Methods, Estimates, and Simulations for France,” Journal of the European Economic Association,19(1), pp. 620-663.
Katic, P. and A. Leigh (2016) “Top Wealth Shares in Australia 1915-2012,” Review of Income & Wealth,62(2), p. 209-222.
Kubota, K. (2017) “Intergenerational Wealth Elasticity in Japan,” Japanese Economic Review, 68(4),pp. 470-496.
Kuhn, M., M. Schularick, and U. I. Steins (2020) “Income and Wealth Inequality in America, 19492016,” Journal of Political Economy, 128(9), pp. 3469-3519.
Lefranc, A., F. Ojima, and T. Yoshida (2014) “Intergenerational Earnings Mobility in Japan Among
Sons and Daughters: Levels and Trends,” Journal of Population Economics, 27(1), pp. 91-134.
Okumura, T. and E. Usui (2016) “Intergenerational Transmission of Skills and Differences in Labor
Market Outcomes for Blacks and Whites” in, Research in Labor Economics, pp. 227-286.
Pfeffer, F. T. and A. Killewald (2018) “Generations of Advantage: Multigenerational Correlations in
Family Wealth,” Social Forces; a Scientific Medium of Social Study & Interpretation, 96(4), pp.
1411-1442.
Piketty, T. (2000) ‘Theories of Persistent Inequality and Intergenerational Mobility,’ Handbook of
Income Distribution, 1, pp. 429-476.
Piketty, T. and G. Zucman (2015) “Wealth and Inheritance in the Long Run” in, Handbook of Income
Distribution: Elsevier, 2, pp. 1303-1368.
Ueda, A. (2009) “Intergenerational Mobility of Earnings and Income in Japan,” B.E. Journal of16Economic Analysis & Policy, 9(1), article 54.
Ishino, T., M. Naoi, M. Seko, and K. Sumida (2020) ‘Parental Asset Transfer Expectations andChildren’s

Asset

Accumulation,’

PDRC

Discussion

Paper

Series,

DP2020-005(https://www.pdrc.keio.ac.jp/publications/dp/6704/).
Hirayama, Y. (2019) “The Stratification of Housing Inheritance in the Context of Japan’s Super-Aging
Homeowner Society,” Journal of Architecture and Planning, 84(760), pp. 1433-1442.

17

Table 1: Descriptive statistics
Children
Mean(S.D.)

Parents’ generation
Mean(S.D.)

Age

36.05(9.585)62.003(10.054)

Female = 1

0.641(0.480)0.569(0.496)0.527(0.500)0.844(0.363)Junior and senior high school

0.197(0.398)0.486(0.500)Junior college/College of technology

0.313(0.464)0.13(0.337)

University and graduate school

0.49(0.500)0.384(0.487)

6.941(5.345)7.476(4.505)

6.269(10.999)

11.87(15.479)

8.105(15.175)

14.811(20.161)

0.667

Marital status = 1(1)

Last educational background

Annual household income
Savings

(2)

(3)
(4)

Financial wealth held
Homeownership = 1(0.472)0.913(0.282)21.996 (142.111)

8.119(70.083)

Ordinance-designated city

0.359

(0.480)0.305(0.460)

Other cities

0.571(0.495)0.59(0.492)

Towns and villages

0.07(0.255)0.105(0.307)

(6)

2.373

(0.756)0.101(0.301)0.27(0.444)0.743(0.437)0.583(0.493)Financial support between parents and children(5)

Place of residence (dummy variable)

Number of siblings(6)

Only child = 1

Location of parents and children (dummy variable)
Living together
Within the same prefecture(6)

Within the same city, town, or village

(6)

N

715

962

Note: The age of the child is that of the subject of the JHPS-G2. Parents’ age is that of the younger of the parents. Annual householdincome, savings, and financial asset holdings are all in millions of yen. Annual household income, savings, and financial asset holdings of theparent generation are all averages for 2016–2018. Financial support of the child generation is the amount received from the parent; financial
support of the parent generation is the amount received from the child (in millions of yen). Annual household income, savings, financial
wealth holdings, financial assistance, and sibling composition and parent-child location of the child generation are for the sample excluding
missing values. The final educational background of the parents is that of the surviving father. (1) Parent: N = 830; (2) Child: N = 670; (3)Child: N = 478; (4) Child: N = 374; (5) Child: N = 700, Parent: N = 886; (6) Child: N = 665.

18

Table 2: Intergenerational transition matrix of financial wealth holdings
Household income quartile of parents’generation (adjusted for sex, age, and marital
status)Quartile of annual household income of children(adjusted for sex, age, and marital status)

Total

I

Ⅱ

Ⅲ

IV

42.4

37

12

8.7

100

24.7

24.7

36

14.6

100

20

25.6

22.2

32.2

100

IV

14.4

11.1

30

44.4

100

Total

25.5

24.7

24.9

24.9

100

I

Ⅱ
Ⅲ

Note: The quartiles of financial asset holdings for the parent and child generations were determined on the basis of the residuals from
regressing the respective financial wealth holdings on age and its square, gender, and marital status. Each cell in the table then shows the resultof calculating the proportions from the results of cross-tabulation by parent and child (sex-, age-, and marital status–adjusted) financial asset
value quartiles so that the row sum is 100.

Table 3: Intergenerational transition matrix of household income
Household income quartile of parents’generation (adjusted for sex, age, and marital
status)I

Ⅱ
Ⅲ

Quartile of annual household income of children(adjusted for sex, age, and marital status)

Total

I

Ⅱ

Ⅲ

IV

36.1

28.9

24.1

10.8

100

23.2

29.3

28

19.5

100

24.1

22.9

26.5

26.5

100

IV

17.1

18.3

22

42.7

100

Total

25.2

24.8

25.2

24.8

100

Note: The household income quartiles for the parent and child generations were determined on the basis of the residuals from regressing therespective household income on age and its square, gender, and marital status. Each cell in the table then shows the results of calculating thepercentages from the results of cross-tabulation by (sex-, age-, and marital status–adjusted) income quartiles for parents and children so thatthe row sum is 100. For the parent generation, the sample is limited to those in which the younger of the parents is 65 years old or younger.

19

Table 4: Intergenerational correlation between parental wealth and child attributes
Parent generation’s wealth holdings (explanatory variable)
Financial wealth holdings (average ofpast three years)
Attributes of the child generation (dep.
var.)
Amount of deposits and savings

Coef.

Adj. R2

Coef.

N(S.E.)

0.1088

0.197

457

0.303

360

0.0012673(0.0012)
College degree or higher = 1

0.0065 ***

0.075

893

0.02720.093

634

0.222 ***

0.052

458

0.4554(over the last year)(0.3272)

0.308

360

0.019

855

0.0688 ***

0.135

438

0.00130.0066 ***0.02420.2381 ***

0.135

673

0.181

346

0.0012 *

0.136

639

0.09

852

0.081

608

0.039

441

0.019

814

0.058

700

0.042

696

(0.0006)
0.076

893

0.0028 ***(0.0007)

0.092

634

0.055

458

0.019

855

0.0244 ***(0.0081)(0.0548)0.42780.1016 ***(0.0255)(0.0177)(0.0511)
Financial support from parents

N(0.0195)**(0.0014)(0.0168)
Savings ratio (%)

457(0.0012)(0.0013)Annual household income

0.194(0.0510)0.136

Adj. R2(S.E.)

0.1253 ***0.1259

Net wealth holdings (average of thepast three years)
Coef.

N

(0.0374)**(0.0483)
Homeownership = 1

Adj. R2(S.E.)

0.1088 ***(0.0370)

Financial wealth

Financial wealth holdings (average ofthe past five years)

0.0516 *(0.0269)(0.3534)

0.213 **
(0.1027)

With future gifts/inheritance = 1
Financial wealth0.0081 ***

0.058

738

0.038

734

(0.0013)
Housing

0.0039 ***(0.0014)0.0087 ***

0.062

738

0.039

734

(0.0014)0.0043 ***(0.0016)0.0032 ***(0.0009)
0.0021 ***(0.0007)

Note: Marginal effects and standard errors of the parental generation’s asset variables on the dependent variable in the table side are reported. Figures in parentheses are cluster-robust standard errors with respect to thehousehold ID of the parent generation. ***, **, and * indicate that the estimated coefficients are significant at the 1%, 5%, and 10% levels, respectively. In all estimations, parent and child age and their squared terms,
child gender, marital status, and parent-child cohabitation dummies are added as explanatory variables. The units for savings, financial wealth holdings, and net asset holdings are all in millions of yen. The unit for financial
support from parents is 10,000 yen.

20

Table 5: Intergenerational correlation between net wealth holdings of parents and financial wealthholdings and homeownership of children
Asset holdings of the child generation (dependent variable)
Financial wealth held
Coef.

Added explanatory variables[1](S.E.)
0.1016 ***Age, gender, marital status, living together

(%)
(100)

(0.0255)[2]

0.0843 ***+ Final education

0.0659 ***+ Income(83)

0.0551 **+ Financial support between parents and children(65)

0.0591 **+ Death of parents(54)

0.0553 **+ Future gifting and inheritance(58)+ Savings ratio[8]+ Parent-child location

0.0364(54)(0.0290)(93)0.0007(65)0.0007(58)

0.0004(31)

0.0001(9)(0.0006)(36)(0.0281)0.03450.0011 *(0.0006)(0.0275)
[7]

(100)

(0.0006)(0.0268)[6]0.0012 *(%)(0.0006)(0.0250)[5](S.E.)(0.0006)(0.0248)
[4]

Coef.

(0.0006)(0.0261)[3]Homeownership = 1

0.0001(10)(0.0006)(34)

0.0002(20)(0.0006)

Note: Results using net asset holdings as the variable for asset holdings of the parent generation. The table summarizes the changes in marginal effects when the explanatory
variables are added sequentially. The “%” column shows the change when the magnitude of the coefficient in Model [1] is set to 100. Figures in parentheses are clusterrobust standard errors for the household ID of the parent generation. ***, **, and * indicate that the estimated coefficients are significant at the 1%, 5%, and 10% levels,
respectively. In all estimations, parent-child age and its squared term, child gender, marital status, and parent-child cohabitation dummies are added as explanatory variables.

21

Table 6: Net wealth holdings of parents’ generation and future gifts and inheritance classified by child’s income
Gifts and inheritance of financial wealth

Gifts and inheritance of housing

Housing wealth

[1]

[2]

[3]

[4]

[5]

[6]

0.0042 **0.0045 **0.0043 ***0.0045 ***0.0042 **0.0037 **(0.0019)(0.0020)(0.0011)(0.0012)(0.0017)(0.0017)

Annual household income (child)
Bottom 10%
Median0.0044***(0.0012)
Top 10%0.00430.0046***(0.0012)***0.00440.0019(0.0008)*****

0.0021(0.0008)***0.0051***(0.0014)0.00020.00010.00530.0047 ***(0.0014)***0.0052 ***(0.0010)(0.0010)(0.0010)(0.0010)(0.0015)(0.0015)

Child attributes

No

Yes

No

Yes

No

Yes

Location attributes

No

Yes

No

Yes

No

Yes

Control variable

N

586

583

586

583

278

277

Note: Marginal effects are shown for parental net wealth holdings. Figures in parentheses are cluster-robust standard errors for parental household ID. ***, **, and * indicate that the estimated coefficients are significant at the
1%, 5%, and 10% levels, respectively. In all estimations, parent and child age and their squared terms, child gender, marital status, and parent-child cohabitation dummies are added as explanatory variables. The control
variables comprise child attributes (number of siblings, only child dummy, and homeownership dummy) and location attributes (city and county size of child’s residence [government-designated city, other city, and townshipdummies], city and county size of parents’ residence, dummy for parent and child living in the same city and county, and dummy for parent and child living in the same prefecture).

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Table 7: Net wealth holdings of parents’ generation and future gifts and inheritance classified by child’s education

Financial wealth

Housing

Housing wealth

[1]

[2]

[3]

[4]

[5]

[6]

0.00260.0055 ***0.0045 ***0.0054 ***0.0016 ***0.0019 **(0.0020)(0.0020)(0.0016)(0.0019)(0.0005)(0.0008)

0.0028 **0.0034 ***0.00180.002

0.0029 ***0.0022 ***(0.0012)(0.0013)(0.0012)(0.0013)(0.0009)(0.0008)

Final education (child)
Junior and senior high school
Junior college/College of technology
University and graduate school

0.0035**0.0035**0.001

0.0012*0.0059***0.0049 ***(0.0015)(0.0015)(0.0007)(0.0007)(0.0018)(0.0017)

Child attributes

No

Yes

No

Yes

No

Yes

Location attributes

No

Yes

No

Yes

No

Yes

Control variable

N

686

601

685

602

330

283

Note: Marginal effects are shown for parental net wealth holdings. Figures in parentheses are cluster-robust standard errors for parental household ID. ***, **, and * indicate that the estimatedcoefficients are significant at the 1%, 5%, and 10% levels, respectively. In all estimations, parent and child age and its squared term, child gender, marital status, education, and parent and childcohabitation dummies are added as explanatory variables. The control variables comprise child attributes (number of siblings, only child dummy, and homeownership dummy) and location attributes(city and county size of the child's residence [government-designated city, other city, and township dummies], city and county size of the parents’ residence, dummy for parent and child living in thesame city and county, and dummy for parent and child living in the same prefecture).

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Table A1: Intergenerational elasticity of household wealthParent generation’s wealth holdings (explanatory variable)
Financial wealth holdings (average ofpast three years)
Attributes of the child generation (dep. var.)
Amount of deposits and savings

Coef.

Adj. R2(S.E.)
0.5522 ***0.197

Financial wealth holdings (average ofthe past five years)
Coef.

N

(S.E.)
0.591 ***

457

(0.1396)
Financial wealth0.5353 ***

0.303

360

0.136

673

0.075

893

0.093

634

0.18230.26120.4573(over the last year)(0.3621)

0.135

673

0.076

893

0.092

634

0.052

458

0.268

855

438

0.7582 ***

0.181

346

0.0595 *

0.136

639

0.1633 ***

0.09

852

0.1355 ***

0.081

608

0.039

441

0.019

814

0.058

700

0.042

696

(0.0484)
***

0.055

458

(0.0588)
0.019

0.135

(0.0411)(0.0512)***N(0.0310)***0.0714(0.0582)
Financial support from parents

360(0.0385)0.0836(0.0509)

Savings ratio (%)

0.308(0.0321)***0.5889 ***2

Adj. R(0.2611)0.0346(0.0388)
Annual household income

457(0.1767)

0.03270.1866(S.E.)(0.2075)

0.5896 ***(0.0320)
College degree or higher = 1

0.194

Coef.

N

(0.1310)(0.1833)
Homeownership = 1

Adj. R2

Net wealth holdings (average of thepast three years)

0.1193 *(0.0633)

0.418

0.019

855

(0.3681)0.3779(0.2372)

With future gifts/inheritance = 1
Financial wealth

0.2259 ***0.058

0.2329 ***738(0.0371)
Housing

0.118

0.062

738

(0.0371)
***

0.038

734

0.1235(0.0428)(0.0439)0.1845 ***(0.0485)

***

0.039

734

0.128 ***
(0.0416)

Note: We report the elasticities and standard errors of the parental generation’s asset variables for the dependent variables in the table side. Figures in parentheses are cluster-robust standard errors with respect to the parental household
ID. ***, **, and * indicate that the estimated coefficients are significant at the 1%, 5%, and 10% levels, respectively. In all estimations, parent and child ages and their squared terms, child gender, marital status, and parent-childcohabitation dummies are added as explanatory variables.

24